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Anomalous diffusion is a phenomenon that cannot be modeled accurately by second-order diffusion equations, but is better described by fractional diffusion models. The nonlocal nature of the fractional diffusion operators makes substantially…

Numerical Analysis · Mathematics 2018-03-08 K. Mustapha , K. Furati , O. M. Knio , O. Le Maitre

A method is given for finding roots of a one-variable function using Taylor's expansion of that function and fractional derivative calculated at a suitable tangent point without using Newton's method, but is regarded as a variant of Halley…

Optimization and Control · Mathematics 2023-03-10 Ali Dorostkar , Ahmad Sabihi

Conventional finite-difference schemes for solving partial differential equations are based on approximating derivatives by finite-differences. In this work, an alternative theory is proposed which view finite-difference schemes as…

Numerical Analysis · Mathematics 2013-09-23 Siu A. Chin

This paper is concerned with mixed finite element method (FEM) for solving the two-dimensional, nonlinear fourth-order active fluid equations. By introducing an auxiliary variable $w=-\Delta u$, the original fourth problem is transformed…

Numerical Analysis · Mathematics 2025-07-30 Nan Zheng , Xu Guo , Wenlong Pei , Wenju Zhao

Derivative-free optimization (DFO) consists in finding the best value of an objective function without relying on derivatives. To tackle such problems, one may build approximate derivatives, using for instance finite-difference estimates.…

Optimization and Control · Mathematics 2024-06-04 Clément W. Royer , Oumaima Sohab , Luis Nunes Vicente

Federated learning (FL) enhances data privacy with collaborative in-situ training on decentralized clients. Nevertheless, FL encounters challenges due to non-independent and identically distributed (non-i.i.d) data, leading to potential…

Machine Learning · Computer Science 2024-01-29 Weiming Zhuang , Lingjuan Lyu

In this paper, we give a detailed account of the algorithm outlined in [1] for Feynman integral reduction and $\varepsilon$-factorised differential equations. The algorithm consists of two steps. In the first step, we use a new geometric…

Derivative-free optimization (DFO) is the mathematical study of the optimization algorithms that do not use derivatives. One branch of DFO focuses on model-based DFO methods, where an approximation of the objective function is used to guide…

Numerical Analysis · Mathematics 2016-12-16 Warren Hare

We prove that the finite-difference based derivative-free descent (FD-DFD) methods have a capability to find the global minima for a class of multiple minima problems. Our main result shows that, for a class of multiple minima objectives…

Optimization and Control · Mathematics 2020-06-26 Xiaopeng Luo , Xin Xu , Daoyi Dong

In this paper, we propose a simple numerical algorithm based on the weak Galerkin (WG) finite element method for a class of fourth-order problems in fluorescence tomography (FT), eliminating the need for stabilizer terms required in…

Numerical Analysis · Mathematics 2025-03-25 Chunmei Wang , Shangyou Zhang

The secant method is a very effective numerical procedure used for solving nonlinear equations of the form $f(x)=0$. It is derived via a linear interpolation procedure and employs only values of $f(x)$ at the approximations to the root of…

Numerical Analysis · Mathematics 2020-12-09 Avram Sidi

Sequential Residual Methods try to solve nonlinear systems of equations $F(x)=0$ by iteratively updating the current approximate solution along a residual-related direction. Therefore, memory requirements are minimal and, consequently,…

Numerical Analysis · Mathematics 2023-04-28 Ernesto G. Birgin , J. M. Martínez

It is known that the Frank-Wolfe (FW) algorithm, which is affine-covariant, enjoys accelerated convergence rates when the constraint set is strongly convex. However, these results rely on norm-dependent assumptions, usually incurring…

Optimization and Control · Mathematics 2020-11-09 Thomas Kerdreux , Lewis Liu , Simon Lacoste-Julien , Damien Scieur

In this paper, we introduce the Deep Finite Volume Method (DFVM), an innovative deep learning framework tailored for solving high-order (order \(\geq 2\)) partial differential equations (PDEs). Our approach centers on a novel loss function…

Numerical Analysis · Mathematics 2024-07-15 Jianhuan Cen , Qingsong Zou

In this paper we construct high order numerical methods for solving third and fourth orders nonlinear functional differential equations (FDE). They are based on the discretization of iterative methods on continuous level with the use of the…

Numerical Analysis · Mathematics 2024-11-05 Dang Quang A , Dang Quang Long

The finite-difference time-domain (FDTD) method is a flexible and powerful technique for rigorously solving Maxwell's equations. However, three-dimensional optical nonlinearity in current commercial and research FDTD softwares requires…

Optics · Physics 2017-12-27 Charles Varin , Rhys Emms , Graeme Bart , Thomas Fennel , Thomas Brabec

In this paper we present a refined Radial Basis Function-generated Finite Difference (RBF-FD) solution for a non-Newtonian fluid in a closed differentially heated cavity. The non-Newtonian behaviour is modelled with the Ostwald-de Waele…

Numerical Analysis · Mathematics 2025-03-24 Miha Rot , Gregor Kosec

In this article I present a fast and direct method for solving several types of linear finite difference equations (FDE) with constant coefficients. The method is based on a polynomial form of the translation operator and its inverse, and…

Numerical Analysis · Mathematics 2011-11-03 S. Merino

Solving the three-dimensional (3D) Bratu equation is highly challenging due to the presence of multiple and sharp solutions. Research on this equation began in the late 1990s, but there are no satisfactory results to date. To address this…

Numerical Analysis · Mathematics 2025-07-22 Muhammad Luthfi Shahab , Hadi Susanto , Haralampos Hatzikirou

The Adomian decomposition method is a semi-analytical method for solving ordinary and partial nonlinear differential equations. The aim of this paper is to apply Adomian decomposition method to obtain approximate solutions of nonlinear…

Numerical Analysis · Mathematics 2017-12-27 Iqra Javed , Ashfaq Ahmad , Muzammil Hussain , S. Iqbal